BlockFaaS: Blockchain-enabled Serverless Computing Framework for AI-driven IoT Healthcare Applications
BlockFaaS: Blockchain-enabled Serverless Computing Framework for AI-driven IoT Healthcare Applications
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DOI：
10.1007/s10723-023-09691-w
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发表时间：
2023-11
影响因子：
5.5
通讯作者：
Muhammed Golec;S. Gill;Mustafa Golec;Minxian Xu;Soumya K. Ghosh;S. Kanhere;Omer F. Rana;Steve Uhlig
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文献类型：
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作者：
Muhammed Golec;S. Gill;Mustafa Golec;Minxian Xu;Soumya K. Ghosh;S. Kanhere;Omer F. Rana;Steve Uhlig
随着新传感器技术的发展，基于物联网（IoT）的医疗保健应用近年来获得了发展势头。然而，物联网设备资源有限，无法执行大型计算操作。为了解决这个问题，无服务器模式凭借其动态可扩展性和基础设施管理等优势，可以用于支持基于物联网的应用程序的需求。然而，由于物联网的异构结构，在提供这种集成时还必须考虑用户信任。这个问题可以通过使用区块链来解决，区块链可以保证数据的不变性，并确保物联网设备生成的任何数据都不会被修改。本文提出了一种BlockFaaS框架，该框架通过将无服务器平台和区块链架构集成到基于延迟敏感人工智能（AI）的医疗保健应用程序中，支持动态可扩展性并保证安全性和隐私性。为此，我们部署了AIBRisk框架，它保证了智能医疗应用程序中的数据不变性，并将其部署到HealthFaaS中，HealthFaaS是一个基于无服务器的心脏病风险检测框架。为了扩展这个框架，我们使用了高性能的AI模型和更高效的区块链模块。我们在所有通信渠道中使用传输层安全（TLS）协议，以确保框架内的隐私。为了验证所提出的框架，我们比较了它的性能与HealthFaaS和AIBEASTM框架。结果显示，BlockFaaS的AUC为4.79%，优于HealthFaaS，并且在区块链模块上消耗的能量比AIBRisk少162.82毫焦耳。此外，还研究了Google Cloud Platform（集成了BlockFaaS的无服务器平台）中发生的冷启动延迟值以及影响该值的因素。
With the development of new sensor technologies, Internet of Things (IoT)-based healthcare applications have gained momentum in recent years. However, IoT devices have limited resources, making them incapable of executing large computational operations. To solve this problem, the serverless paradigm, with its advantages such as dynamic scalability and infrastructure management, can be used to support the requirements of IoT-based applications. However, due to the heterogeneous structure of IoT, user trust must also be taken into account when providing this integration. This problem can be overcome by using a Blockchain that guarantees data immutability and ensures that any data generated by the IoT device is not modified. This paper proposes a BlockFaaS framework that supports dynamic scalability and guarantees security and privacy by integrating a serverless platform and Blockchain architecture into latency-sensitive Artificial Intelligence (AI)-based healthcare applications. To do this, we deployed the AIBLOCK framework, which guarantees data immutability in smart healthcare applications, into HealthFaaS, a serverless-based framework for heart disease risk detection. To expand this framework, we used high-performance AI models and a more efficient Blockchain module. We use the Transport Layer Security (TLS) protocol in all communication channels to ensure privacy within the framework. To validate the proposed framework, we compare its performance with the HealthFaaS and AIBLOCK frameworks. The results show that BlockFaaS outperforms HealthFaaS with an AUC of 4.79% and consumes 162.82 millijoules less energy on the Blockchain module than AIBLOCK. Additionally, the cold start latency value occurring in Google Cloud Platform, the serverless platform into which BlockFaaS is integrated, and the factors affecting this value are examined.